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AFT - AGENTFLY TECHNOLOGIES
AgentFly Technologies is a technology and research company specializing in the simulation and control of unmanned aerial systems and air traffic management simulation. The company performs research, development, and operations in four main areas: UAS Integration into Shared Airspace (UTM) consists of building advanced software tools, algorithms, and simulations for UAS operators, regulators, and service providers. Offered algorithms include advanced control of autonomous UAS, trajectory planning in complex environments, including geofencing, conflict detection and resolution, and integration of UAS into shared airspace. Simulation is used to assess capacity, performance characteristics and benchmarking C2C and other components of the UTM ecosystem.
ATM Modeling and Simulation provides a large-scale simulation of tens of thousands of aircraft, physical and navigation environments, and cognitive model of air traffic controllers.
Military and security operations utilize drones in complex systems for aerial protection of assets, intelligence, surveillance, target acquisition, and other tactical missions. Aerial work automation focuses on the automation of the whole processing chain - 3D trajectory planning, data acquisition, multiple sensor data fusion, and post-processing.
Role in the project
The main role of AgentFly Technologies is to validate the environmental, socioeconomic and safety impact indicators developed in the ImAFUSA project through simulations.
AFT will provide its in-house agent-based fast-time large-scale ATM/UAM/U-space simulator that is developed in cooperation with FAA and was successfully deployed in numerous R&D projects. Simulator will be extended to allow integration of models of environmental, socioeconomic and safety metrics and indicators along with their assessment tools. Improved simulation will enable the design of rich use case scenarios and validation and verification of proposed ImAFUSA framework within an advanced simulation environment using an agent-based models while considering complex 3D environment, environmental factors, technical parameters, services provided and involved stakeholders. Comparison of nominal scenarios and extended scenarios with ImAFUSA framework will be carried out to assess positive impact of new indicators on public acceptance and to verify there will be no negative impact on overall performance of the U-space ecosystem.
